Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has developed into an important tool in the armoury of diagnostic imaging. The use of a contrast agent allows additional information to be obtained. If the biological uptake of the contrast agent is monitored by repeated scanning, dynamic information can be obtained that is not achievable with conventional MRI. The benefit of functional and vascular information is clear when we consider, for example, tumour angiogenesis. In many organs, such as the liver, a growing tumour will soon require a substantial blood supply and to do this it stimulates arterial growth at its boundary. This arterial growth will be both disordered and disorganised. A contrast agent in its first arterial pass through the body will flow around the tumour periphery creating a ring-shaped enhancement pattern. The under-developed blood vessels leak contrast agent and the pattern of enhancement yields quantitative information on these processes. For example, see Choyke et al.: Functional tumor imaging with dynamic contrast-enhanced magnetic resonance imaging (J Magn Reson Imaging 17(5) (May 2003) 509-520); Cuenod et al.: Tumor angiogenesis: pathophysiology and implications for contrast-enhanced MRI and CT assessment (Abdom Imaging 31(2) (2006) 188-193); and Tofts et al.: Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols (J Magn Reson Imaging 10(3) (September 1999) 223-232).
DCE-MRI often takes minutes to capture the image, which means that the patient will often move and will certainly need to breathe over the course of a scan. Registration is often needed to align images taken with the patient in different positions. Registration methods often assume that features in two images are the same, and the alignment of these features uses simple image or information based cost-functions. The assumption of recurring features cannot be made in DCE-MRI; in the simplest case differences exist between pre-contrast and post-contrast images: enhanced features such as tumour boundaries will not be present in the pre-contrast images. There have been a number of attempts at a solution to this problem.
One method restricts any registration that attempts to introduce rapid volume changes (associated with an enhancing boundary) as described by both Tanner et al. (Volume and shape preservation of enhancing lesions when applying non-rigid registration to a time series of contrast enhancing MR breast images, Lect. Notes Comput. Sc. 1935 (2000) 327-337) and Rohlfing et al. (Volume-preserving non-rigid registration of MR breast images using free-form deformation with an incompressibility constraint, IEEE Trans Med Imaging 22(6) (June 2003) 730-741).
Alternatively, Buonaccorsi et al. (Comparison of the performance of tracer kinetic model-driven registration for dynamic contrast enhanced MRI using different models of contrast enhancement, Acad Radiol 13(9) (September 2006) 1112-1123) propose an iterative registration method that allows registration of the original data to a synthetic data series. The process allows the production of more suitable target images to which to register. The synthetic data is generated by fitting the Kety pharmacokinetic model to the original data (Buckley, D. L.: Uncertainty in the analysis of tracer kinetics using dynamic contrast-enhanced t1-weighted MRI, Magn Reson Med 47(3) (March 2002) 601-606). The registered data is used to update the pharmacokinetic model, which is then used to generate the synthetic data for the next registration step. A small region of interest is used, and only rigid deformations are considered.
There is need for a method which circumvents the requirement for a model. The present invention addresses this need and provides a method which generates a synthetic time-series using data-reduction techniques. The present invention allows a large region of interest to be considered without the complications of either segmentation or multiple model-fitting.